typhoon-ai/gigaspeech2-typhoon

Gigaspeech2 Typhoon

Project page | Paper | GitHub

Gigaspeech2 Typhoon is a metadata-only reference dataset for Thai speech recognition benchmarking, specifically designed as an Accuracy Track for evaluating ASR models. The dataset contains 1,000 test samples with audio IDs and human transcriptions derived from the Gigaspeech2 corpus. Each audio_id directly links to the original Gigaspeech2 dataset, allowing users to download the corresponding audio.

Dataset Overview

• Language: Thai
• Domain: Audio from Gigaspeech2
• Samples: 1,000 test samples
• Format: Metadata-only (audio_id + sentence)
• Task: ASR Accuracy Evaluation (Accuracy Track)
• License: CC-BY 4.0 (inherited from Gigaspeech2)
• Original Source: speechcolab/gigaspeech2
• Audio Access: Download from original Gigaspeech2 using audio_id

Dataset Structure

The dataset contains a single test split intended for evaluation purposes only.

Data Fields

• audio_id (string): Unique identifier linking directly to Gigaspeech2 audio samples (e.g., 63-63248-21)
• sentence (string): Human-transcribed Thai text

Note: This is a metadata-only dataset. Audio files are not included. To obtain the audio, download from speechcolab/gigaspeech2 using the audio_id.

Data Statistics

• Total samples: 1,000
• Average transcription length: 48.16 characters
• Min/Max transcription length: 5 / 123 characters
• Average word count: 2.00 words
• Min/Max word count: 1 / 11 words

Example

from datasets import load_dataset

dataset = load_dataset("typhoon-ai/gigaspeech2_typhoon")

# Access the test split
test_data = dataset['test']

# View a sample
print(test_data[0])
# {
#   'audio_id': '63-63248-21',
#   'sentence': 'มันมาทางซ้ายแล้วก็พุ่งไปทางฝั่งขวามือข้างหน้ารถเขาอะฮะ'
# }

# To get the actual audio, download from original Gigaspeech2:
# original_gs2 = load_dataset("speechcolab/gigaspeech2", streaming=True)
# Then match using audio_id

Attribution

This dataset is a curated subset derived from the original speechcolab/gigaspeech2 dataset. All audio samples in this dataset:

• Originate from the Gigaspeech2 Thai corpus
• Follow the Gigaspeech2 audio ID convention (e.g., 63-63248-21)
• Maintain the same Creative Commons licensing as the source

Original Dataset Citation

Please also cite the original Gigaspeech2 paper:

@inproceedings{gigaspeech2,
  title={GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement},
  author={Yifan Yang and Zheshu Song and Jianheng Zhuo and Mingyu Cui and Jinpeng Li and Bo Yang and Yexing Du and Ziyang Ma and Xunying Liu and Ziyuan Wang and Ke Li and Shuai Fan and Kai Yu and Wei-Qiang Zhang and Guoguo Chen and Xie Chen},
  booktitle={Proc. ACL},
  year={2025},
  address={Vienna},
}

Verification: All audio IDs in this dataset conform to the Gigaspeech2 naming convention and are traceable to the original corpus.

Limitations

• Test-only dataset: Contains only 1,000 samples intended for evaluation, not for training
• Metadata-only: Audio files not included - users must download from original Gigaspeech2
• Clean audio focus: Represents clean, academic-style speech from Gigaspeech2
• Size: Relatively small dataset suitable for benchmarking but not comprehensive coverage
• Domain specificity: Academic-style speech may differ from conversational or spontaneous speech

Citation

If you use this dataset in your research or application, please cite our technical report:

@misc{warit2026typhoonasr,
      title={Typhoon ASR Real-time: FastConformer-Transducer for Thai Automatic Speech Recognition}, 
      author={Warit Sirichotedumrong and Adisai Na-Thalang and Potsawee Manakul and Pittawat Taveekitworachai and Sittipong Sripaisarnmongkol and Kunat Pipatanakul},
      year={2026},
      eprint={2601.13044},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2601.13044}, 
}

Contact

For questions or feedback about this dataset, please visit opentyphoon.ai or open an issue on the dataset repository.